Detect if your browser fingerprint, Canvas, WebGL and more can be identified
Browser fingerprinting identifies and tracks users based on the unique combination of settings and capabilities exposed by their browser and device. Unlike cookies, it requires no stored data and is difficult to clear, making it one of the most persistent tracking techniques on the modern web.
A browser fingerprint is a collection of attributes describing your device's software and hardware configuration. Instead of storing an identifier on your device the way cookies do, a website reads dozens of signals — screen resolution, language, time zone, installed fonts, graphics hardware and more — and combines them into a single profile. Because the specific combination is rarely shared by two devices, that profile can recognise you on return visits and link your activity across sites, even after you clear your browser data.
When a page loads, scripts query the browser through standard JavaScript APIs. Each answer — your user-agent string, color depth, CPU core count, touch support, available fonts — adds a few bits of identifying information. No single value is unique, but entropy accumulates: combine fifteen or twenty weakly-identifying signals and the result is often unique among millions of users. The site hashes these values into a stable ID and stores it on the server, completely outside your control.
Canvas fingerprinting asks your browser to render hidden text or shapes to an off-screen canvas, then reads back the pixel data. Tiny differences in your GPU, graphics driver, and anti-aliasing produce a rendering that is consistent for your device but varies between machines. WebGL fingerprinting goes further, probing your 3D graphics stack for the renderer name, supported extensions, and shading precision. Together these are among the highest-entropy signals available to trackers.
Fingerprinting is not limited to graphics. The AudioContext API can be used to process a silent waveform whose output varies subtly by hardware and operating system. Font enumeration detects which typefaces you have installed, often revealing your OS and applications. Other vectors include battery status, media device labels, hardware concurrency, and timing measurements. Trackers blend many of these vectors so that even if you mask one, the rest still identify you.
Fingerprinting powers cross-site advertising, fraud scoring, and account linking — frequently without consent and invisibly to the user. For people who rely on privacy, such as journalists or researchers, a distinctive fingerprint can undermine other protections like a VPN or private browsing. For businesses running multiple accounts, a shared fingerprint across profiles is the single most common reason platforms flag and ban those accounts.
The counter-intuitive goal is to look ordinary, not invisible. Browsers like Tor and Brave deliberately make many users share the same fingerprint, so blending in beats standing out. Anti-detect browsers create isolated profiles with consistent, plausible fingerprints for each identity. Avoid rare extensions, exotic fonts, and unusual screen sizes, keep your browser updated, and test regularly — a script that spoofs one value but leaves contradictions elsewhere can make you more identifiable, not less.
The quickest way to check your browser fingerprint is to run a test that reads the same signals trackers collect — your canvas and WebGL hashes, fonts, screen and hardware details, audio stack, and User-Agent — and combines them into a single identifier. Our fingerprint check does this entirely in your browser, with no data sent to a server, and shows how unique each signal is so you can see exactly which attributes make you stand out. Re-checking after a browser update or an extension change is the only reliable way to confirm whether your fingerprint actually shifted.
Phones are often assumed to be more private than desktops, but Android and iOS browsers are fingerprintable too. Mobile devices expose device pixel ratio, sensor APIs, installed fonts, GPU model, and touch capabilities, and because most users keep the stock browser and default settings, mobile fingerprints can be surprisingly stable. The trade-off differs from desktop: there is less hardware variety, so any single phone looks more like its peers, but cross-checking the mobile fingerprint against the User-Agent quickly reveals spoofed or emulated environments. You can run the same fingerprint check on Android or iPhone to see your mobile signals.
In most regions fingerprinting itself is not illegal, but using it to track people for advertising typically falls under privacy laws such as the GDPR and ePrivacy Directive, which require a lawful basis and often consent. Enforcement varies widely, and many sites use it with little transparency.
No. Private browsing only prevents your browser from saving local history and cookies. Your fingerprint — screen, hardware, fonts, GPU — is exactly the same in a private window, so a tracker can still recognise your device. Private mode protects against local snooping, not remote fingerprinting.
Only partially. A VPN changes your IP address and approximate location, but your fingerprint is built from browser and hardware signals that a VPN does not touch. You can appear to come from another country while still presenting the same fingerprint, which is itself a detectable inconsistency.
It depends on your configuration, but studies have found that a large majority of desktop browsers are uniquely identifiable. Running our fingerprint check shows which of your signals carry the most entropy, so you can see exactly what makes your device stand out from the crowd.
Run a browser fingerprint check. It collects your canvas, WebGL, font, audio, screen, and hardware signals in the browser and hashes them into an identifier, then estimates how unique that combination is. Our check runs fully client-side, so nothing is uploaded, and it highlights the highest-entropy signals so you know which attributes to address first.
Yes. Mobile browsers expose GPU, screen, font, sensor, and User-Agent data that can be combined into a fingerprint just like on desktop. Phones have less hardware diversity, so an individual device blends in more, but the fingerprint is still stable enough to recognise you across sessions, and inconsistencies between the mobile signals and the User-Agent are easy to detect.
